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The Extreme Scale Engineering and Discovery Environment (XSEDE) is an NSF-funded service that provides computing resources to institutions across the country. XSEDE is an open scientific discovery infrastructure combining leadership class resources at eleven partner sites to create an integrated, persistent computational resource.

ARC-TS participates in the XSEDE Campus Champion program, facilitating access to the organization’s resources. Contact Brock Palen for more information.

For general information on XSEDE, visit the XSEDE home page.

Order Service

Visit the XSEDE User Portal for information on getting an XSEDE allocation.

Related Event

May 31 @ 9:00 am - 4:30 pm

Introduction to SPSS

Audience: Never before SPSS users who will be using SPSS for Windows.  Those using SPSS for Unix or Macintosh should email the instructor at cpow@umich.edu before enrolling. Note: Topic order is subject…

June 11 @ 10:00 am - 12:00 pm

Introduction to Deep Neural Networks with Keras/Tensorflow

Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level, Python interface running on top of multiple neural network libraries,…

June 15 @ 2:00 pm - 4:45 pm

Classification, Regression and Model Selection using Python’s Scikit-learn

This workshop will introduce participants to machine learning in Python. We’ll start with a brief explanation of Anaconda and the Jupyter notebook environment (although not required for the participant, the…

June 22 @ 1:00 pm - 4:30 pm

Spatial point process models

This is the first workshop in a series of three workshops that will cover spatial modeling of three broad classes of data: (i) spatial point pattern, (ii) discrete spatial variation…